Real World Data (RWD) has various types of data sources, but each source has a different format and terminology code, which makes analysis process cumbersome and repetitive. The OMOP Common Data Model (CDM) is an open standard for analysis of RWD on a global scale, and the OHDSI community is responsible for its maintenance and development. What sets the OMOP CDM apart from other data standards is the way in which it has created a structure for integrating and handling terminology globally, and the way in which analysis is conducted without exposing individual patient information outside. Such features facilitate international collaboration. The method of not releasing patient data outside is expected to be widely utilized in future because it is highly compatible with Japan's pseudonymously processed information (PPI) based on the personal information protection act, in which PPI data cannot be provided to any third party but the purpose of use can be easily changed. There are many advantages not only for international collaboration, but also for domestic collaboration or in-house use. Epidemiologists and data scientists will be able to handle data in the same model they are accustomed to both domestically and internationally. That will be of great benefit to students, personnel, and their organizations especially when they study abroad, return home, or transfer internationally. Globally, collaborators from more than 70 countries are working on this project. Data on more than 800 million people after eliminating estimated duplicates, or 10％ of the world's population, has been converted to the OMOP CDM. More than 250 related published articles have been registered with PubMed. On the other hand in Japan, there are many issues to be solved, such as support system and terminology mapping. To catch up with international levels, strong cooperation from a wide range of fields is needed.

Objective：The objective of this study was to apply Least Absolute Shrinkage and Selection Operator （LASSO）logistic regression to detection of adverse drug reaction （ADR） signals using an electronic health records database as a comprehensive and quantitative method to supplement the current pharmacovigilance activities in Japan.

Design：case-control study

Methods：We analyzed data from 40767 inpatients using a single-institution hospital database and identified two ADRs, suspected pancreatitis and thrombocytopenia, using abnormal laboratory test results. LASSO logistic regression analysis was applied to detect ADR signals with adjustment for age, sex, comorbidities and medical procedures. The positive predictive value （PPV） was calculated using reference standard of known drug-ADR associations based on drug product labels.

Results：The number of case group was 6735 for suspected pancreatitis and 11561 for thrombocytopenia. The number of ADR signals detected using LASSO logistic regression was 27 for suspected pancreatitis and 40 for thrombocytopenia. The calculated PPV was 3.7% for suspected pancreatitis and 55.0% for thrombocytopenia.

Conclusion：LASSO logistic regression analysis efficiently detects ADR signals by adjusting for confounding factors such as comorbidities and medical procedures. The false positive signals may contain unknown signals and further signal assessment will be needed.

A thirteen-day-old neonate was admitted because of systolic heart murmur, tachycardia, tachypnea and sucking weakness. The chest X-ray film demonstrated remarkable cardiomegaly and pulmonary congestion. Echocardiography detected marked thickening and stenosis of the aortic valve, and left ventricular dysfunction (EF=10%). The pressure gradient between left ventricle and ascending aorta was presumed 130mmHg with pulsed Doppler echocardiography, Since he did not respond to conservative treatment, an emergency open aortic valvular commissurotomy under cardiopulmonary bypass was performed the day after admission. We made incisions of 1mm in the left side and 0.5mm in the right side commissure of the adherent bicuspid aortic valve. After the procedure, left ventricular function improved (EF=57%), and the pressure gradient was reduced to 62mmHg. He showed good recover from the congestive heart failure. There are few reports about operative treatment of congenital aortic valve stenosis in neonates. This is considered to be the third youngest successful operative case of open aortic valvular commissurotomy in Japan.

Prostaglandin E₁ (PGE₁) was used continuously in adults from immediately after induction of anesthesia, during extracorporeal circulation, to the acute phase after open heart surgery. Using blood flow in the toe determined by laser Doppler flowmeter and the temperature difference between periphery and core as indices, the effects of afterload reduction and improvement of peripheral circulation were investigated. Subjects were 17 adults who underwent open heart surgery. PGE₁ was used in 7 patients and not used in 10. In the group using PGE₁, continuous injection of 0.015μg/kg/min of PGE₁ was started immediately after induction of anesthesia and was maintained during extracorporeal circulation until the acute phase after surgery. During extracorporeal circulation, perfusion pressure was kept at 50∼60mmHg and PGE₁ injection was controlled within the range of 0.015∼0.030μg/kg/min. At completion of extracorporeal circulation, the dose was fixed at 0.015μg/kg/min again. The degree of improvement of peripheral circulation was evaluated on the basis of hemodynamics, blood flow in the toe determined by laser Doppler flowmeter and the temperature difference between periphery and core, at induction of anesthesia (before using PGE₁) on completion of extracorporeal circulation, and in the acute phase after surgery. The value of blood flow in the toe determined by laser Doppler flowmeter was significantly higher in the PGE₁ group than in the non-PGE₁ group, from completion of extracorporeal circulation to the acute phase after surgery. Moreover, peripheral temperature was significantly higher in the PGE₁ group than in the non-PGE₁ group at completion of the extracorporeal circulation as well as immediately after surgery, and the temperature difference between periphery and core was significantly smaller. Continuous injection of PGE₁ enabled smooth control of perfusion pressure during extracorporeal circulation. Although there was no significant difference in peripheral vascular and total pulmonary resistance, the coefficients tended to be lower in the PGE₁ group. The use of PGE₁ during open heart surgery seems to be an effective method to improve peripheral circulation.

Objective：The objective of this study was to apply Least Absolute Shrinkage and Selection Operator （LASSO）logistic regression to detection of adverse drug reaction （ADR） signals using an electronic health records database as a comprehensive and quantitative method to supplement the current pharmacovigilance activities in Japan.Design：case-control studyMethods：We analyzed data from 40767 inpatients using a single-institution hospital database and identified two ADRs, suspected pancreatitis and thrombocytopenia, using abnormal laboratory test results. LASSO logistic regression analysis was applied to detect ADR signals with adjustment for age, sex, comorbidities and medical procedures. The positive predictive value （PPV） was calculated using reference standard of known drug-ADR associations based on drug product labels.Results：The number of case group was 6735 for suspected pancreatitis and 11561 for thrombocytopenia. The number of ADR signals detected using LASSO logistic regression was 27 for suspected pancreatitis and 40 for thrombocytopenia. The calculated PPV was 3.7% for suspected pancreatitis and 55.0% for thrombocytopenia.Conclusion：LASSO logistic regression analysis efficiently detects ADR signals by adjusting for confounding factors such as comorbidities and medical procedures. The false positive signals may contain unknown signals and further signal assessment will be needed.